{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as patches"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 柱状图"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## version I"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAW4AAAD8CAYAAABXe05zAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAACjhJREFUeJzt3c+rZ3d9x/HXuxlFEysKuRuTTCdCsRWhRC4lGnCRuGir6KaLFCLUzWxajSKIduM/IKKLIgyxbgy6GLMoItaCuugmdCYJaDIWJGoSjXhd+AM3MfjuYq4kM7l37om5x+/3PffxgIGZm++9vDjMPDlz5n7zqe4OAHP82aYHAPDyCDfAMMINMIxwAwwj3ADDCDfAMMINMIxwAwwj3ADDnFrji95888195syZNb40wHXp4sWLv+junSWvXSXcZ86cyYULF9b40gDXpar68dLXelQCMIxwAwwj3ADDCDfAMMINMIxwAwwj3ADDCDfAMKu8AQfgulJ1vF/vFZ71644bYBjhBhhGuAGGEW6AYYQbYBjhBhhGuAGGEW6AYYQbYBjhBhhGuAGGEW6AYYQbYBjhBhhGuAGGEW6AYYQbYBjhBhhmUbir6qNV9XhVfa+qvlxVr1l7GAAHOzLcVXVLkg8n2e3utyW5Icm9aw8D4GBLH5WcSvLaqjqV5MYkP11vEgDXcmS4u/snST6d5Kkkzyb5VXd/8+rXVdXZqrpQVRf29vaOfykASZY9KnljkvcnuT3Jm5LcVFX3Xf267j7X3bvdvbuzs3P8SwFIsuxRybuT/LC797r7d0keSvLOdWcBcJgl4X4qyZ1VdWNVVZJ7klxadxYAh1nyjPvhJOeTPJLku/ufc27lXQAc4tSSF3X3p5J8auUtACzgnZMAwwg3wDDCDTCMcAMMI9wAwwg3wDDCDTCMcAMMI9wAwwg3wDDCDTCMcAMMI9wAwwg3wDDCDTCMcAMMs+ggBYCNqDrer9d9vF9vQ9xxAwwj3ADDCDfAMMINMIxwAwwj3ADDCDfAMMINMIxwAwwj3ADDCDfAMMINMIxwAwwj3ADDCDfAMMINMIxwAwyzKNxV9YaqOl9V36+qS1X1jrWHAXCwpUeXfS7JN7r7H6vq1UluXHETANdwZLir6vVJ3pXkn5Oku59L8ty6swA4zJJHJW9Ospfki1X1aFU9UFU3rbwLgEMsCfepJG9P8vnuviPJb5N84uoXVdXZqrpQVRf29vaOeSbwJ1d1vD84NkvC/UySZ7r74f1fn8/lkF+hu89192537+7s7BznRgBe5Mhwd/fPkjxdVW/Z/9A9SZ5YdRUAh1r6XSUfSvLg/neUPJnkg+tNAuBaFoW7ux9LsrvyFgAW8M5JgGGEG2AY4QYYRrgBhhFugGGEG2AY4QYYRrgBhhFugGGEG2AY4QYYRrgBhhFugGGEG2AY4QYYRrgBhhFugGGEG2AY4QYYRrgBhhFugGGEG2AY4QYYRrgBhhFugGGEG2AY4QYYRrgBhhFugGGEG2AY4QYYRrgBhhFugGGEG2AY4QYYZnG4q+qGqnq0qr625iAAru3l3HHfn+TSWkMAWGZRuKvq1iTvSfLAunMAOMrSO+7PJvl4kt+vuAWABY4Md1W9N8nPu/viEa87W1UXqurC3t7esQ2EE6fqeH9w3Vlyx31XkvdV1Y+SfCXJ3VX1patf1N3nunu3u3d3dnaOeSYAf3BkuLv7k919a3efSXJvkm91932rLwPgQL6PG2CYUy/nxd39nSTfWWUJAIu44wYYRrgBhhFugGGEG2AY4QYYRrgBhhFugGGEG2AY4QYYRrgBhhFugGGEG2AY4QYYRrgBhhFugGGEG2AY4QYY5mWdgAOrOO6TyLtn74AjuOMGGEa4AYYRboBhhBtgGOEGGEa4AYYRboBhhBtgGOEGGEa4AYYRboBhhBtgGOEGGEa4AYYRboBhhBtgGOEGGObIcFfVbVX17aq6VFWPV9X9f4phABxsydFlzyf5WHc/UlV/nuRiVf13dz+x8jYADnDkHXd3P9vdj+z//DdJLiW5Ze1hABzsZT3jrqozSe5I8vAaYwA42uJT3qvqdUm+muQj3f3rA/772SRnk+T06dPHNpAVOdUcRlp0x11Vr8rlaD/Y3Q8d9JruPtfdu929u7Ozc5wbAXiRJd9VUkm+kORSd39m/UkAXMuSO+67knwgyd1V9dj+j39YeRcAhzjyGXd3/0+SY34YCsAfyzsnAYYRboBhhBtgGOEGGEa4AYYRboBhhBtgGOEGGEa4AYYRboBhhBtgGOEGGEa4AYYRboBhhBtgGOEGGEa4AYZZfMr7K7YtJ4pvw45t2ACM5Y4bYBjhBhhGuAGGEW6AYYQbYBjhBhhGuAGGEW6AYYQbYBjhBhhGuAGGEW6AYYQbYBjhBhhGuAGGEW6AYYQbYJhF4a6qv6uq/6uqH1TVJ9YeBcDhjgx3Vd2Q5N+T/H2Styb5p6p669rDADjYkjvuv03yg+5+srufS/KVJO9fdxYAh1kS7luSPP2iXz+z/zEANmDJKe8HHUn+kmPFq+pskrNJcvr06QM+Y0tOIt+GHduwIbHjanZcaRt2bMOGZHt27Ftyx/1Mktte9Otbk/z06hd197nu3u3u3Z2dnePaB8BVloT7f5P8ZVXdXlWvTnJvkv9cdxYAhznyUUl3P19V/5rkv5LckOQ/uvvx1ZcBcKAlz7jT3V9P8vWVtwCwgHdOAgwj3ADDCDfAMMINMIxwAwxTvcI7gqpqL8mP/8hPvznJL45xzmSuxZVcjyu5Hi+4Hq7FX3T3oncvrhLuV6KqLnT37qZ3bAPX4kqux5VcjxectGvhUQnAMMINMMw2hvvcpgdsEdfiSq7HlVyPF5yoa7F1z7gBuLZtvOMG4Bq2JtwOJH5BVd1WVd+uqktV9XhV3b/pTZtWVTdU1aNV9bVNb9m0qnpDVZ2vqu/v/x55x6Y3bVJVfXT/z8n3qurLVfWaTW9a21aE24HEL/F8ko91918nuTPJv5zw65Ek9ye5tOkRW+JzSb7R3X+V5G9ygq9LVd2S5MNJdrv7bbn8v56+d7Or1rcV4Y4Dia/Q3c929yP7P/9NLv/BPLHnfFbVrUnek+SBTW/ZtKp6fZJ3JflCknT3c939y82u2rhTSV5bVaeS3JgDTui63mxLuB1IfIiqOpPkjiQPb3bJRn02yceT/H7TQ7bAm5PsJfni/qOjB6rqpk2P2pTu/kmSTyd5KsmzSX7V3d/c7Kr1bUu4Fx1IfNJU1euSfDXJR7r715veswlV9d4kP+/ui5vesiVOJXl7ks939x1JfpvkxP6bUFW9MZf/dn57kjcluamq7tvsqvVtS7gXHUh8klTVq3I52g9290Ob3rNBdyV5X1X9KJcfod1dVV/a7KSNeibJM939h7+Bnc/lkJ9U707yw+7e6+7fJXkoyTs3vGl12xJuBxK/SFVVLj/DvNTdn9n0nk3q7k92963dfSaXf198q7uv+zuqw3T3z5I8XVVv2f/QPUme2OCkTXsqyZ1VdeP+n5t7cgL+sXbRmZNrcyDxS9yV5ANJvltVj+1/7N/2z/6EDyV5cP8m58kkH9zwno3p7oer6nySR3L5u7EezQl4F6V3TgIMsy2PSgBYSLgBhhFugGGEG2AY4QYYRrgBhhFugGGEG2CY/wcXOSQ2y29kvwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "y = np.random.randint(0,10,(10))\n",
    "y = sorted(y)\n",
    "plt.vlines(np.arange(10),ymin=0, ymax=y,\n",
    "           colors='r',linestyles='solid',\n",
    "          linewidth=20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## exercise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_raw = pd.read_csv(\"https://github.com/selva86/datasets/raw/master/mpg_ggplot2.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df_raw[[\"cty\",\"manufacturer\"]].groupby(\"manufacturer\").mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.sort_values('cty',inplace=True)\n",
    "df.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(12,8),dpi=60)\n",
    "ax = fig.add_axes((0.1,0.13,0.8,0.77))\n",
    "\n",
    "# draw bar chart\n",
    "ax.vlines(x=df.index, ymin=0, ymax=df.cty, \n",
    "          color='firebrick', alpha=.7, linewidth=10)\n",
    "\n",
    "# set text\n",
    "for x,y in zip(df.index,df.cty):\n",
    "    ax.text(x,y+0.5,round(y,1),\n",
    "           va='center',ha='center')\n",
    "\n",
    "# draw patch\n",
    "p1 = patches.Rectangle((.546,0), \n",
    "                       width=0.35,height=0.13,\n",
    "                       color='g',alpha=.1,\n",
    "                      transform=fig.transFigure)\n",
    "p2 = patches.Rectangle((0.1,0),\n",
    "                      width=0.446,height=0.13,\n",
    "                      alpha=.1,color='r',\n",
    "                      transform=fig.transFigure)\n",
    "fig.add_artist(p1)\n",
    "fig.add_artist(p2)\n",
    "\n",
    "# set title\n",
    "ax.set_title('Bar Chart for Highway Mileage',fontsize=22)\n",
    "\n",
    "# set xlael\n",
    "ax.set_ylabel('Miles Per Gallon')\n",
    "ax.set_ylim(0,30)\n",
    "\n",
    "# set tick\n",
    "ax.set_xticks(df.index)\n",
    "ax.set_xticklabels(df.manufacturer,\n",
    "                   rotation=45,ha='right',fontsize=12)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 棒棒糖图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_raw = pd.read_csv(\"https://github.com/selva86/datasets/raw/master/mpg_ggplot2.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df_raw[[\"cty\",\"manufacturer\"]].groupby(\"manufacturer\").mean()\n",
    "df.sort_values('cty',inplace=True)\n",
    "df.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(12,8),dpi=60)\n",
    "ax = fig.add_axes((0.1,0.1,0.8,0.8))\n",
    "\n",
    "# draw bar chart\n",
    "ax.vlines(x=df.index, ymin=0, ymax=df.cty, \n",
    "          color='firebrick', alpha=.7, linewidth=1)\n",
    "\n",
    "# plot scatter\n",
    "ax.scatter(df.index,df.cty, color='firebrick')\n",
    "\n",
    "# annotate\n",
    "for x,y in zip(df.index,df.cty):\n",
    "    ax.text(x,y+0.8,round(y,1),fontsize=12,va='center',ha='center')\n",
    "\n",
    "# set title\n",
    "ax.set_title('Lollipop Chart for Highway Mileage',fontsize=14)\n",
    "\n",
    "# set label\n",
    "ax.set_ylabel('Miles Per Gallon')\n",
    "\n",
    "# set xaxis tick\n",
    "ax.xaxis.set_ticks(df.index)\n",
    "ax.xaxis.set_ticklabels(df.manufacturer,rotation=45,ha='right')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 包点图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_raw = pd.read_csv(\"https://github.com/selva86/datasets/raw/master/mpg_ggplot2.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df_raw[[\"cty\",\"manufacturer\"]].groupby(\"manufacturer\").mean()\n",
    "df.sort_values('cty',inplace=True)\n",
    "df.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x480 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(12,8),dpi=60)\n",
    "ax = fig.add_axes((0.1,0.1,0.8,0.8))\n",
    "\n",
    "# draw bar chart\n",
    "ax.hlines(y=df.index, xmin=11, xmax=25, \n",
    "          color='firebrick', alpha=.3, linewidth=1,\n",
    "         linestyle='dashed')\n",
    "\n",
    "# plot scatter\n",
    "ax.scatter(df.cty,df.index, color='firebrick')\n",
    "\n",
    "# set title\n",
    "ax.set_title('Lollipop Chart for Highway Mileage',fontsize=14)\n",
    "\n",
    "# set label\n",
    "ax.set_xlabel('Miles Per Gallon')\n",
    "\n",
    "# set xaxis tick\n",
    "ax.yaxis.set_ticks(df.index)\n",
    "ax.yaxis.set_ticklabels(df.manufacturer)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 坡度图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.lines as lines"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_raw = pd.read_csv(\"https://github.com/selva86/datasets/raw/master/gdppercap.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>continent</th>\n",
       "      <th>1952</th>\n",
       "      <th>1957</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Africa</td>\n",
       "      <td>1252.572466</td>\n",
       "      <td>1385.236062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Americas</td>\n",
       "      <td>4079.062552</td>\n",
       "      <td>4616.043733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Asia</td>\n",
       "      <td>5195.484004</td>\n",
       "      <td>4003.132940</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Europe</td>\n",
       "      <td>5661.057435</td>\n",
       "      <td>6963.012816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Oceania</td>\n",
       "      <td>10298.085650</td>\n",
       "      <td>11598.522455</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  continent          1952          1957\n",
       "0    Africa   1252.572466   1385.236062\n",
       "1  Americas   4079.062552   4616.043733\n",
       "2      Asia   5195.484004   4003.132940\n",
       "3    Europe   5661.057435   6963.012816\n",
       "4   Oceania  10298.085650  11598.522455"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_raw"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "left_label = [x+','+str(round(y)) for x,y in zip(df_raw.continent,df_raw['1952'])]\n",
    "right_label = [x+','+str(round(y)) for x,y in zip(df_raw.continent,df_raw['1957'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 480x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(8,12),dpi=60)\n",
    "ax = fig.add_axes((0.1,0.1,0.8,0.8))\n",
    "\n",
    "# draw vline\n",
    "ax.vlines(x=1, ymin=500,ymax=13000, \n",
    "          linestyles='dotted', color='k',alpha=.7, linewidth=1)\n",
    "ax.vlines(x=3, ymin=500,ymax=13000, \n",
    "          linestyles='dotted', color='k',alpha=.7, linewidth=1)\n",
    "\n",
    "# plot scatter\n",
    "ax.scatter(x=np.repeat(1,df_raw.shape[0]),y=df_raw['1952'],\n",
    "           s=10, color='k',alpha=.7)\n",
    "ax.scatter(x=np.repeat(3,df_raw.shape[0]),y=df_raw['1957'],\n",
    "           s=10, color='k',alpha=.7)\n",
    "\n",
    "# connect points and put text \n",
    "for y1,y2,le,rg in zip(df_raw['1952'],df_raw['1957'],left_label,right_label):\n",
    "    l = lines.Line2D([1,3],[y1,y2],\n",
    "                 color='r' if y1>y2 else 'g',\n",
    "                markersize=5,\n",
    "                marker='o')\n",
    "    ax.add_line(l)\n",
    "    ax.text(1-0.05,y1,le,ha='right',fontsize=12)\n",
    "    ax.text(3+0.05,y2,rg,ha='left',fontsize=12)\n",
    "\n",
    "ax.text(1,13000,'BEFORE',\n",
    "        fontsize=14,fontweight='semibold',va='bottom',ha='center')\n",
    "ax.text(3,13000,'AFTER',\n",
    "        fontsize=14,fontweight='semibold',va='bottom',ha='center')\n",
    "\n",
    "# set xlim\n",
    "ax.set_xlim(0,4)\n",
    "\n",
    "# set xaxis tick\n",
    "ax.xaxis.set_ticks(np.array([1,3]))\n",
    "ax.xaxis.set_ticklabels(['1952','1957'])\n",
    "\n",
    "# set yaxis tick\n",
    "ax.yaxis.set_ticks(np.arange(500,13000,2000))\n",
    "\n",
    "# set title\n",
    "ax.set_title(\"Slopechart: Comparing GDP Per Capita between 1952 vs 1957\", \n",
    "             fontdict={'size':22})\n",
    "\n",
    "# lighten yaxis ticks\n",
    "for tick in ax.yaxis.get_major_ticks():\n",
    "    tick.tick1line.set(visible=False)\n",
    "\n",
    "# lighten borders\n",
    "for spine in ax.spines.values():\n",
    "    spine.set(alpha=0.0)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 哑铃图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.lines as lines"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_raw = pd.read_csv(\"https://github.com/selva86/datasets/raw/master/health.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Area</th>\n",
       "      <th>pct_2014</th>\n",
       "      <th>pct_2013</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Houston</td>\n",
       "      <td>0.19</td>\n",
       "      <td>0.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Miami</td>\n",
       "      <td>0.19</td>\n",
       "      <td>0.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Dallas</td>\n",
       "      <td>0.18</td>\n",
       "      <td>0.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>San Antonio</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Atlanta</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Tampa</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Riverside, Calif.</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Phoenix</td>\n",
       "      <td>0.13</td>\n",
       "      <td>0.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Charlotte</td>\n",
       "      <td>0.13</td>\n",
       "      <td>0.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>San Diego</td>\n",
       "      <td>0.12</td>\n",
       "      <td>0.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>All Metro Areas</td>\n",
       "      <td>0.11</td>\n",
       "      <td>0.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Chicago</td>\n",
       "      <td>0.11</td>\n",
       "      <td>0.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>New York</td>\n",
       "      <td>0.10</td>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Denver</td>\n",
       "      <td>0.10</td>\n",
       "      <td>0.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Washington, D.C.</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Portland</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>St. Louis</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Detroit</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Seattle</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>San Francisco</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Baltimore</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Pittsburgh</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Minneapolis</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Boston</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 Area  pct_2014  pct_2013\n",
       "0             Houston      0.19      0.22\n",
       "1               Miami      0.19      0.24\n",
       "2              Dallas      0.18      0.21\n",
       "3         San Antonio      0.15      0.19\n",
       "4             Atlanta      0.15      0.18\n",
       "5         Los Angeles      0.14      0.20\n",
       "6               Tampa      0.14      0.17\n",
       "7   Riverside, Calif.      0.14      0.19\n",
       "8             Phoenix      0.13      0.17\n",
       "9           Charlotte      0.13      0.15\n",
       "10          San Diego      0.12      0.16\n",
       "11    All Metro Areas      0.11      0.14\n",
       "12            Chicago      0.11      0.14\n",
       "13           New York      0.10      0.12\n",
       "14             Denver      0.10      0.14\n",
       "15   Washington, D.C.      0.09      0.11\n",
       "16           Portland      0.09      0.13\n",
       "17          St. Louis      0.09      0.10\n",
       "18            Detroit      0.09      0.11\n",
       "19       Philadelphia      0.08      0.10\n",
       "20            Seattle      0.08      0.12\n",
       "21      San Francisco      0.08      0.11\n",
       "22          Baltimore      0.06      0.09\n",
       "23         Pittsburgh      0.06      0.07\n",
       "24        Minneapolis      0.06      0.08\n",
       "25             Boston      0.04      0.04"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_raw"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_raw.sort_values('pct_2014',inplace=True)\n",
    "df_raw = df_raw.reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>Area</th>\n",
       "      <th>pct_2014</th>\n",
       "      <th>pct_2013</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>25</td>\n",
       "      <td>Boston</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>23</td>\n",
       "      <td>Pittsburgh</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>22</td>\n",
       "      <td>Baltimore</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>24</td>\n",
       "      <td>Minneapolis</td>\n",
       "      <td>0.06</td>\n",
       "      <td>0.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>21</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>20</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>19</td>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>18</td>\n",
       "      <td>Detroit</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>17</td>\n",
       "      <td>St. Louis</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>16</td>\n",
       "      <td>Portland</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>15</td>\n",
       "      <td>Washington, D.C.</td>\n",
       "      <td>0.09</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>14</td>\n",
       "      <td>Denver</td>\n",
       "      <td>0.10</td>\n",
       "      <td>0.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>New York</td>\n",
       "      <td>0.10</td>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>12</td>\n",
       "      <td>Chicago</td>\n",
       "      <td>0.11</td>\n",
       "      <td>0.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>11</td>\n",
       "      <td>All Metro Areas</td>\n",
       "      <td>0.11</td>\n",
       "      <td>0.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>10</td>\n",
       "      <td>San Diego</td>\n",
       "      <td>0.12</td>\n",
       "      <td>0.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>9</td>\n",
       "      <td>Charlotte</td>\n",
       "      <td>0.13</td>\n",
       "      <td>0.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>8</td>\n",
       "      <td>Phoenix</td>\n",
       "      <td>0.13</td>\n",
       "      <td>0.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>7</td>\n",
       "      <td>Riverside, Calif.</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>6</td>\n",
       "      <td>Tampa</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>5</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>0.14</td>\n",
       "      <td>0.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>4</td>\n",
       "      <td>Atlanta</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>3</td>\n",
       "      <td>San Antonio</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2</td>\n",
       "      <td>Dallas</td>\n",
       "      <td>0.18</td>\n",
       "      <td>0.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1</td>\n",
       "      <td>Miami</td>\n",
       "      <td>0.19</td>\n",
       "      <td>0.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0</td>\n",
       "      <td>Houston</td>\n",
       "      <td>0.19</td>\n",
       "      <td>0.22</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    index               Area  pct_2014  pct_2013\n",
       "0      25             Boston      0.04      0.04\n",
       "1      23         Pittsburgh      0.06      0.07\n",
       "2      22          Baltimore      0.06      0.09\n",
       "3      24        Minneapolis      0.06      0.08\n",
       "4      21      San Francisco      0.08      0.11\n",
       "5      20            Seattle      0.08      0.12\n",
       "6      19       Philadelphia      0.08      0.10\n",
       "7      18            Detroit      0.09      0.11\n",
       "8      17          St. Louis      0.09      0.10\n",
       "9      16           Portland      0.09      0.13\n",
       "10     15   Washington, D.C.      0.09      0.11\n",
       "11     14             Denver      0.10      0.14\n",
       "12     13           New York      0.10      0.12\n",
       "13     12            Chicago      0.11      0.14\n",
       "14     11    All Metro Areas      0.11      0.14\n",
       "15     10          San Diego      0.12      0.16\n",
       "16      9          Charlotte      0.13      0.15\n",
       "17      8            Phoenix      0.13      0.17\n",
       "18      7  Riverside, Calif.      0.14      0.19\n",
       "19      6              Tampa      0.14      0.17\n",
       "20      5        Los Angeles      0.14      0.20\n",
       "21      4            Atlanta      0.15      0.18\n",
       "22      3        San Antonio      0.15      0.19\n",
       "23      2             Dallas      0.18      0.21\n",
       "24      1              Miami      0.19      0.24\n",
       "25      0            Houston      0.19      0.22"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_raw"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 480x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(8,12),dpi=60)\n",
    "ax = fig.add_axes((0.1,0.1,0.8,0.8))\n",
    "\n",
    "# draw vlines\n",
    "ax.vlines(x=0.05,ymin=0, ymax=28,linestyle='dotted')\n",
    "ax.vlines(x=0.1,ymin=0, ymax=28,linestyle='dotted')\n",
    "ax.vlines(x=0.15,ymin=0, ymax=28,linestyle='dotted')\n",
    "ax.vlines(x=0.20,ymin=0, ymax=28,linestyle='dotted')\n",
    "ax.vlines(x=0.25,ymin=0, ymax=28,linestyle='dotted')\n",
    "\n",
    "# plot scatter\n",
    "ax.scatter(df_raw['pct_2013'],df_raw.index,\n",
    "           color='#0e668b',alpha=0.7,s=50)\n",
    "ax.scatter(df_raw['pct_2014'],df_raw.index,\n",
    "           color='#a3c4dc',alpha=0.7,s=50)\n",
    "\n",
    "# contect points\n",
    "for x1,x2,y in zip(df_raw.pct_2013,df_raw.pct_2014,df_raw.index):\n",
    "    l = lines.Line2D([x1,x2],[y,y])\n",
    "    ax.add_line(l)\n",
    "\n",
    "# set axes background color \n",
    "ax.set(facecolor='#f7f7f7')\n",
    "fig.set(facecolor='#f7f7f7')\n",
    "\n",
    "# set xaxis tick\n",
    "ax.xaxis.set_ticks(np.arange(0.05,0.3,0.05))\n",
    "ax.xaxis.set_ticklabels(['5%','10%','15%','20%','25%'])\n",
    "\n",
    "# set title\n",
    "ax.set_title(\"Dumbell Chart: Pct Change - 2014 vs 2013\", \n",
    "             fontsize=22)\n",
    "\n",
    "# set y_label\n",
    "ax.set_ylabel('Mean GDP Per Capita',fontsize=14)\n",
    "\n",
    "\n",
    "\n",
    "# set yaxis tick\n",
    "ax.set_ylim(-1,26)\n",
    "ax.yaxis.set_ticks(range(25))\n",
    "ax.yaxis.set_ticklabels(df_raw.Area)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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